Background: In the image processing area, deblurring and denoising are the most challenging hurdles. The deblurring image by a spatially invariant kernel is a frequent problem in the field of image processing. Methods: For deblurring and denoising, the total variation (TV norm) and nonlinear anisotropic diffusion models are powerful tools. In this paper, nonlinear anisotropic diffusion models for image denoising and deblurring are proposed. The models are developed in the following manner: first multiplying the magnitude of the gradient in the anisotropic diffusion model, and then apply priori smoothness on the solution image by Gaussian smoothing kernel. Results: The finite difference method is used to discretize anisotropic diffusion models with forward-backward diffusivities. Conclusion: The results of the proposed model are given in terms of the improvement.
机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Chang, QS
Chern, IL
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机构:Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Chang, QS
Chern, IL
论文数: 0引用数: 0
h-index: 0
机构:Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China